Contemplating the Effect of Ambient Temperature Variation on SoC Estimation of Li-NMC Battery

In this paper, a lucid technique to estimate the State of Charge (SoC) of Lithium-Ion battery, subjected to ambient temperature variation is proposed. Equivalent Circuit Modelling (ECM) is the most widely used strategy to emulate the battery performance attributes. Typically, the ECM parametric data is predominantly acquired under constant temperature test conditions. However, batteries under the influence of ambient temperature variation may exhibit stochastic behaviour, which causes the actual battery parameters to deviate from the ECM parameters. This discrepancy between the actual battery and the ECM renders the SoC estimation to be erroneous. Hence this paper explores the effect of ambient temperature variation on Lithium-Nickel-Manganese-Cobalt-Oxide (Li-NMC) battery and suggests a cogent twitch (rebound) voltage analysis methodology to devise an Enriched Extended Kalman Filter control algorithm to appropriately estimate the SoC with minimal error bounds.

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